TESIS DOCTORAL
Design, Development and Evaluation of
a Robotic Platform for Gait
Rehabilitation and Training in Patients
with Cerebral Palsy
Autor:
Cristina Bayón Calderón
Director:
Eduardo Rocon de Lima
Tutor:Luis Enrique Moreno Lorente
DOCTORADO INGENIERÍA ELÉCTRICA, ELECTRÓNICA Y AUTOMÁTICA
TESIS DOCTORAL
DESIGN, DEVELOPMENT AND EVALUATION OF A ROBOTIC
PLATFORM FOR GAIT REHABILITATION AND TRAINING IN
PATIENTS WITH CEREBRAL PALSY
Autor:
Cristina Bayón CalderónDirector:
Eduardo Rocon de LimaFirma del Tribunal Calificador:
Firma Presidente: Vocal: Secretario: Calificación: Leganés, Marzo de 2018
Platform for Gait Rehabilitation and Training in
Patients with Cerebral Palsy
Cristina Bay´on Calder´on
-RJ
Mitte-No es que no quiera, es que no quiero querer. -Joaqu´ın
Sabina-No tengo palabras para describir todo lo que he sentido en estos cuatro a˜nos y lo mucho que ha significado para m´ı el desarrollo de esta tesis doctoral. Hay tanta gente detr´as de este trabajo, que casi me parece imposible poder nombrarlos a todos.
En primer lugar, y aunque no formen parte de la vida profesional, empezar´e por agrade-cer a mi familia su apoyo incondicional desde el primer d´ıa, en el que ni yo misma estaba segura de querer emprender este camino de mi vida; y a Carlos, porque le debo mucho, y es la persona que me ha sabido comprender mejor que nadie durante todo este tiempo. En estos a˜nos en el CSIC, he tenido la oportunidad de conocer gente excepcional, los cuales me aceptaron desde el primer d´ıa dentro de un grupo de trabajo envidiable. Me gustar´ıa expresar mis agradecimientos a todos los que compartieron conmigo momentos, primero en el grupo de Bioingenier´ıa y m´as tarde en el grupo gNEC. Gracias al ambiente creado por estas personas, tanto dentro como fuera del trabajo, mi adaptaci´on fue muy sencilla.
A los que se marcharon antes que yo, gracias por dejar huella en mi vida: Bea, gracias por saber escucharme. Rafa, eres la mejor persona que he conocido nunca; soy muy afortunada por tenerte como amigo. ´Oscar, sabes que la mitad de esta tesis es tuya; tuve la enorme suerte de poder realizar este trabajo junto a ti.
Tambi´en quiero agradecer a los compa˜neros de Chicago y Holanda el apoyo que me ofrecieron durante las estancias doctorales. En especial a la Dr. Deborah Gaebler, porque verla trabajar derrochando ese entusiasmo, fue un gusto que dif´ıcilmente pueda repetirse. Tambi´en al Dr. Edwin van Asseldonk, quien siempre regala energ´ıa positiva, y gracias a ello me hizo disfrutar de nuevo del mundo de la investigaci´on con un proyecto tan impresionante como es el LOPES. Edwin, como dijimos, eres capaz de “mover” a las personas sin necesidad de un robot.
El proyecto CPWalker es fruto de la colaboraci´on de muchos profesionales, sin los cuales, todo habr´ıa sido diferente: gracias gNEC, IBV y a todos los componentes del equipo del HNJ que disfrutaron junto a m´ı de las pruebas cl´ınicas. Sus ganas inmensas hicieron que
Mis agradecimientos m´as especiales van para los verdaderos superh´eroes de esta historia: todos los ni˜nos con PC, que de una forma u otra me han cambiado la vida. Ellos me han aportado enormes valores que nunca voy a ser capaz de devolverles. La ilusi´on con la que afrontan cada d´ıa, y su colaboraci´on incondicional en este proyecto, les hace ser enormes.
Finalmente, pero a´un con m´as fuerza, quisiera dar las gracias a mi Maestro. Eduardo, desde el primer momento tuvimos una conexi´on especial que hizo que todo fluyera como lo ha hecho. Gracias por arriesgarte conmigo en esta etapa innolvidable. S´olo t´u sabes todo lo que he sentido durante este tiempo, has estado a mi lado en los momentos buenos y no tan buenos, y siempre sac´andome una sonrisa. Me has ense˜nado much´ısimo, y gracias a tu carisma, tu personalidad y tu esfuerzo, este grupo de personas a´un sigue en pie. Pase lo que pase en el futuro, no te voy a olvidar.
I have no words to describe all that I have felt in these four years and how much this thesis has meant to me. There are so many people behind this work, so it is nearly impossible to include them all.
First, and although they are not part of my professional life, I want to acknowledge my family and the unconditional support that they have given me since day one, when I was not even sure I wanted to undertake this path in my life; also to Carlos, because I owe him a lot, and he is the person who has best understood me for these four years. During this period in the CSIC, I have had the opportunity of meeting extraordinary people, who work in an enviable workgroup. I would like to acknowledge all the people who shared any moments with me, previously in the Bioengineering group and sub-sequently in the gNEC Lab. My adaptation was very easy thanks to the atmosphere created by all of them (both inside and outside work).
To the ones that left the group before me, thank you for making a mark on my life: Bea, thank you for your support listening to me. Rafa, you are the best person I have ever met; I am very lucky to have you as my friend. ´Oscar, you know that half of this thesis is yours; it was a pleasure to carry out this job with you.
I would also like to acknowledge all the Labs members from Chicago and The Nether-lands, for all the support that I received during the research visits. Specially to Dr. Deborah Gaebler because seeing her enthusiasm working with kids was a pleasure that I will probably never see again. Also to Dr. Edwin van Asseldonk, who always gives o↵ positive energy, and it made me enjoy the world of research once again with an incredible project such as LOPES. Edwin, as we said, you are able to “move” people without the aid of a robot.
The CPWalker project is the result of the collaboration of several professionals working together, and without them, everything would have been di↵erent: thanks gNEC, IBV and all the members of the HNJ team, who enjoyed the clinical tests with me. Their
My special acknowledgements go to the real superheroes of this story: all the children with CP who have changed my life in di↵erent ways. They have given me immense values that I will never be able to give them back. Their happiness to see the life and their unconditional collaboration in this project, make them incredible.
Finally, but most importantly, I would like to recognize my “Maestro”. Eduardo, from the first day we had a special connection that made everything go as it did. Thank you for taking a chance with me in this unforgettable experience. Only you know all that I have felt, you have been with me for the best and the worst moments, always managing to make me smile. I have learned a lot from you, and thanks to your personality and your e↵ort, the Lab continues working successfully. Whatever happens in the future, I will never forget you.
La Par´alisis Cerebral (PC) es un conjunto de alteraciones neurol´ogicas debidas a una lesi´on cerebral surgida en la infancia, que afectan de forma permanente al movimiento de la persona y a su coordinaci´on motora. En algunos casos, estas limitaciones pueden ir acompa˜nadas de problemas sensoriales o intelectuales, dependiendo de la severidad de la lesi´on. Es la discapacidad f´ısica m´as com´un en pacientes pedi´atricos, con una prevalencia de 2.11 casos por 1000 nacimientos. Los tratamientos convencionales de la PC pueden dividirse en tres pilares principales (fisioterapia, terapia ocupacional y logopedia), los cuales deben progresar cada d´ıa en busca de ofrecer mejores resultados a los pacientes. Como parte de la mejora de estos tratamientos convencionales, la terapia por asistencia rob´otica de la marcha es un concepto que ha surgido en los ´ultimos a˜nos para comple-mentar la terapia f´ısica convencional de personas con problemas motores, como aquellos derivados de la PC. Sin embargo, el uso de entrenadores rob´oticos est´a a´un limitado en la pr´actica cl´ınica: los cl´ınicos y familiares demandan m´as investigaciones que confirmen la efectividad de la terapia rob´otica, as´ı como estudios que determinen si la rehabilitaci´on rob´otica realmente merece la pena.
El objetivo principal de esta tesis doctoral es ofrecer una novedosa soluci´on rob´otica para la rehabilitaci´on de la marcha de pacientes pedi´atricos con PC y des´ordenes similares. El enfoque que se pretende dar con el dispositivo rob´otico propuesto en la tesis es distinto al que existe hasta el momento, aportando nuevas ideas no s´olo sobre el dise˜no y el control del dispositivo, sino tambi´en sobre los protocolos de intervenci´on cl´ınica. La metodolog´ıa utilizada para alcanzar este objetivo se bas´o en un estudio detallado sobre la aplicaci´on de entrenadores rob´oticos de rehabilitaci´on elaborados en los ´ultimos a˜nos. Con esta investigaci´on se identificaron las principales limitaciones y desaf´ıos de las terapias rob´oticas actuales, los cuales sirvieron para sentar las bases del dise˜no y desarrollo de una nueva plataforma rob´otica englobada en el marco de trabajo de esta tesis: CPWalker.
CPWalker est´a compuesto por dos partes principales: un andador inteligente y un ex-oesqueleto con 6 grados de libertad. A trav´es de ellas, es posible proporcionar soporte
El entrenador rob´otico CPWalker promueve la progresi´on de pacientes con PC dentro del tratamiento de rehabilitaci´on, incrementando el nivel de intensidad y frecuencia de los ejercicios, al mismo tiempo que aumenta la motivaci´on del usuario y adapta la terapia a las posibilidades de cada paciente. Para ello, utiliza estrategias de control innovadoras, las cuales pueden ser seleccionadas de forma individual para cada articulaci´on, dando as´ı una alta versatilidad en la definici´on de los tratamientos.
La plataforma rob´otica desarrollada fue evaluada tanto t´ecnica como cl´ınicamente con pacientes pedi´atricos. Los resultados muestran el potencial del dispositivo como her-ramienta de rehabilitaci´on, proporcionando tambi´en soporte preliminar para futuras implementaciones cl´ınicas, no solo en CPWalker, sino tambi´en en otros dispositivos rob´oticos de la marcha.
El trabajo desarrollado en esta tesis ha sido llevado a cabo con la ayuda financiera del Ministerio de Econom´ıa y Competitividad espa˜nol y la Secretar´ıa de Estado de Inves-tigaci´on, Desarrollo e Innovaci´on, bajo el contrato BES-2013-064225/DPI2012-39133-C03-01.
Cerebral Palsy (CP) is a set of neurological disorders derived from a brain lesion oc-curred in infancy or early childhood, which permanently a↵ect body movement and muscle coordination. In some cases, these limitations go together with sensory or intel-lectual problems, which depend on the severity of the disease. CP is the most common physical disability in childhood, presenting a prevalence of 2.11 cases per 1000 births. Conventional treatments for CP could be divided in three main pillars (physiotherapy, occupational therapy and speech therapy), which must be continuously improved looking for better results for the patients.
As part of the enrichment of these conventional treatments, robot-assisted gait therapy is a promising tool that has appeared in the last years to complement conventional physical therapy of people with gait disorders as those derived from CP. However, the use of robotic trainers in pediatric clinical practice is still limited: clinicians and families demand further research that confirms the e↵ectiveness of robotic therapy, and clarifies if robotic rehabilitation is worthwhile for their children.
The main objective of this doctoral thesis is to provide a novel robotic solution for gait rehabilitation of pediatric population with CP and related disorders. The approach that the proposed robotic device expects to o↵er is di↵erent from those existing so far, providing new ideas not only about the design and control of the device, but also about clinical intervention protocols. The methodology used to reach this objective was based on a detailed study about the application of robotic trainers developed in the last years for CP rehabilitation. This research identified the main limitations and challenges of current robotic therapies, which served as the base to design and develop a novel robotic platform in the framework of this thesis: CPWalker.
CPWalker is composed by two main parts: a smart walker and an exoskeleton with 6 degrees of freedom. Through them, it is possible to provide user’s partial body weight support in parallel with guided joint motion and over-ground displacement.
enhancing the motivation and tailoring the therapy to each user. To do so, innovative control strategies were used, which may be individually selected per joint giving a high versatility for the treatment’s design.
The developed robotic platform was evaluated both technically and in clinical envi-ronments with pediatric patients. The results show the potential of the novel robotic platform to serve as a rehabilitation tool, also providing preliminary support for future clinical implementations not only in CPWalker, but also in other existing robotic gait trainers.
The work developed in this dissertation has been carried out with the financial support from the Ministerio de Econom´ıa y Competitividad of Spain and the Secretar´ıa de Estado de Investigaci´on, Desarrollo e Innovaci´on, under Contract BES-2013-064225/DPI2012-39133-C03-01.
Nomenclature xxxi
Objectives, Motivation and Organization of Work 1
1 Introduction to Cerebral Palsy and Gait Rehabilitation 5
1.1 Cerebral Palsy . . . 5
1.2 Classification of Cerebral Palsy . . . 6
1.3 Current therapies for patients with CP . . . 9
1.3.1 Physical and occupational therapy . . . 10
1.3.2 Oral medication and botulinum toxin . . . 10
1.3.3 Orthoses and technical supports . . . 10
1.3.4 Orthopaedic surgery . . . 11
1.3.5 Robotic physical therapy . . . 13
1.4 State-of-the-art of robotic devices for rehabilitation in CP . . . 14
1.4.1 Robot-assisted rehabilitation for upper limbs . . . 15
1.4.2 Robot-assisted rehabilitation for lower limbs. . . 17
1.5 Conclusions . . . 22
2 Design of a Robot-Assisted Gait Trainer for Children with Cerebral Palsy: CPWalker 27 2.1 Users’ requirements and layout . . . 29
2.1.1 Discussion group and interviews . . . 30
2.1.2 Design requirements . . . 31
2.2 Robotic platform for gait rehabilitation and training in children with CP 32 2.2.1 Biomechanics of human walking . . . 33
2.2.2 Conceptual design of CPWalker . . . 34
2.3 Mechanical design of CPWalker . . . 36
2.3.1 Smart Walker . . . 38
2.3.1.1 Structure . . . 39
2.3.1.2 Drive system . . . 39
Actuators: . . . 40
Sensors: . . . 40
2.3.1.3 Partial body weight support system . . . 40
Actuators: . . . 41
Sensors: . . . 41
2.3.1.4 System for the adaptation of hip height . . . 41
Actuators: . . . 42
Sensors: . . . 42
2.3.2 Exoskeleton . . . 42
2.3.2.1 Structure . . . 43
2.3.2.2 Exoskeleton joints system . . . 45
Actuators: . . . 45
Sensors: . . . 46
2.4 Control Architecture . . . 48
2.4.1 Control unit. . . 50
2.5 Conclusions . . . 52
3 Development and Preliminary Validation of Robot-Based Rehabilita-tion Therapies with CPWalker Platform 55 3.1 Multimodal Human-Robot interface of CPWalker . . . 56
3.2 Control strategies for robot-based therapies . . . 59
3.2.1 Low-level: gait guiding strategies . . . 61
3.2.1.1 Position control strategy . . . 62
3.2.1.2 Selective impedance control strategy . . . 64
3.2.1.3 Force control strategy . . . 67
3.2.1.4 Technical evaluation of gait guiding strategies . . . 68
3.2.2 Mid-level: multi-joint performance-based adaptive algorithm . . . 70
3.2.2.1 Technical evaluation of performance-based adaptive al-gorithm . . . 75
3.2.3 High-level: biofeedback strategy for postural control . . . 75
3.2.3.1 Technical evaluation of the biofeedback strategy for pos-tural control . . . 78
3.3 Clinician interface of CPWalker . . . 80
3.4 Preliminary locomotor training in pediatric population through CPWalker 83 3.4.1 Patients . . . 84
3.4.2 Therapy . . . 84
3.4.3 Results . . . 86
3.5 Application of the performance-based adaptive algorithm to LOPES II gait trainer . . . 88
3.5.1 LOPES II robotic trainer . . . 88
3.5.2 Improvements of the performance-based adaptive algorithm . . . . 89
3.5.2.1 Subtask-based besides joint-based . . . 89
3.5.2.2 Tolerance zone around the challenge . . . 91
3.5.2.3 Six levels of assistance . . . 92
3.5.3 Preliminary implementation . . . 92
3.5.3.1 Participants . . . 92
3.5.3.2 Protocol . . . 93
3.5.3.3 Analysis . . . 93
3.5.3.4 Results and discussion. . . 94
E↵ects on kinematics: . . . 94
E↵ects of walking speed and PBWS on the users’ perfor-mance without robotic assistance: . . . 94
E↵ects of walking speed and PBWS on the performance-based adaptive controller: . . . 96
3.6 Conclusions . . . 97
4 Gait Training Proposal: Goal Setting, Clinical Implementation, Re-sults and Discussion 101 4.1 Robot-based gait training therapy . . . 102
4.1.1 Robotic training program . . . 104
4.1.1.1 Duration of the study . . . 106
4.1.1.2 Training phases . . . 106
Tailored Assist as Needed strategies: . . . 108
4.1.1.3 Postural control . . . 110
4.1.1.4 Motivation and inclusion of challenges . . . 111
4.1.2 Metrics . . . 111
4.2 Validation with pediatric population . . . 114
4.2.1 Patients’ recruitment. . . 114
4.2.2 Results . . . 115
4.2.2.1 Gait speed, endurance and global responses . . . 116
4.2.2.2 Strength progression. . . 118
4.2.2.3 Kinematics and spatiotemporal variability . . . 118
4.2.2.4 ROM performance . . . 119
4.2.2.5 Qualitative variables. . . 121
4.2.2.6 Patients’ judgement . . . 121
4.3 Discussion and conclusion . . . 122
5 Conclusion and Future Directions 125 5.1 Contributions . . . 125
5.2 CPWalker in perspective and future work . . . 127
5.2.1 CPWalker in perspective. . . 127
5.2.2 Future work. . . 128
5.2.2.1 Improvement of mechanical design . . . 128
5.2.2.2 Improvement of human-robot interaction . . . 129
5.2.2.3 Definition of novel treatment protocols . . . 129
5.2.2.4 Robotics as assessment . . . 130 5.2.2.5 Maximise impact. . . 130 5.3 Scientific dissemination . . . 130 5.3.1 Publications. . . 130 5.3.1.1 Journal articles. . . 130 5.3.1.2 Conference proceedings . . . 131 5.3.1.3 Book chapters . . . 133
5.3.1.4 Other dissemination activities . . . 133
5.3.2 International experience . . . 135
1.1 Types of CP depending on structures involved. . . 7
1.2 Levels of Gross Motor Function Classification System (GMFCS). . . 9
1.3 Types of orthoses for children with movement disorders. (a) Foot thoses (FO); (b) Ankle Foot orthoses (AFO); (c) Knee Ankle Foot or-thoses (KAFO); (d) Hip Knee Ankle Foot oror-thoses (HKAFO). . . 11
1.4 Types of walkers for children with movement disorders. (a) Anterior walker; (b) Posterior walker.. . . 12
1.5 Treatment applied during the growth of children with CP. Frequency peak for SEMLS is achieved in puberty stage. . . 12
1.6 Sti↵ knee flexo in a patient with CP. . . 13
1.7 Robots for upper limbs rehabilitation. (a) InMotion (Interactive Motion Technologies); (b) HapicMaster; (c) Armeo (Hocoma AG); (d) YouGrab-ber (YouRehab); (e) REAPlan. . . 16
1.8 Robotic-assisted gait trainers in CP. (a) NF-Walker; (b) Innowalk-Pro; (c)Lokomat; (d) GT1RehaStim; (e) Walkbot; (f) Autoambulator; (g) Multi-robot. . . 20
2.1 Main purposes for the rehabilitation improvement with the proposed novel robotic platform. . . 28
2.2 Requirements for the new concept of robotic gait trainer and their relative importance given by the people involved in the discussion group. . . 32
2.3 Gait cycle diagram and gait subtasks (grey blocks) focused on right stride. 33
2.4 Overview of CPWalker concept. . . 36
2.5 Parametric CAD model of CPWalker: smart walker and exoskeleton. . . . 38
2.6 Smart Walker structure of CPWalker. . . 39
2.7 Drive system of CPWalker platform. . . 39
2.8 System for the control of user’s weight. . . 40
2.9 System for the control of hip height. . . 42
2.10 Anatomical planes and displacement ranges allowed by the exoskeleton of CPWalker.. . . 43
2.11 Range of measures of CPWalker exoskeleton. . . 44
2.12 User wearing the exoskeleton system. . . 45
2.13 Harmonic drive exploded view. . . 46
2.14 Simulated deformation in the rods of the exoskeleton of CPWalker when a force of 20 N is applied on the extreme. The finite methods calculation defines the proper position of the selected strain gauges (R1, R2, R3 and R4), which is the zone that su↵ers more e↵orts (light blue and green). . . 47
2.15 CPWalker overall control architecture: clinician interface, control unit and robotic platform. All sensors in both exoskeleton legs communi-cate to PC104-I through a CAN bus (deterministic real-time) network (CAN1). Motor drivers of the exoskeleton are connected to a D/A board of the PC104-I. PC104-II is responsible for the control of the traction and body-weight support systems. Drivers for controlling the motors of these systems and for reading their sensors are communicated with PC104-II via another CAN bus (CAN2). PC104-I and PC104-II together constitute the control unit of CPWalker platform. Both PC104 systems are connected to a WiFi hub that enables the communication of both controllers with an external device or tablet that executes the clinician interface and allows clinicians to access information of CPWalker and to control it. . . 49
2.16 Communication architecture between control unit and both systems: ex-oskeleton and walker. Dotted lines indicate CAN bus signals and solid lines indicate analog signals. . . 51
3.1 Scheme correlation between injury to PWM + CSTs and its interferences with volitional movements in children with CP. . . 56
3.2 CPWalker platform and the technology used in the multimodal human-robot interface (MHRI): force sensors, electroencephalography unit, iner-tial sensors for postural control and laser range finder. . . 58
3.3 General control scheme developed to implement gait rehabilitation strate-gies through CPWalker robotic platform.. . . 59
3.4 Hierarchical framework for elemental control strategies of CPWalker plat-form. At the high level, only the postural control strategy is within the framework of this thesis. . . 60
3.5 Scheme of controllers according to “robot in charge” or “patient in charge” levels. From less to more patient’s collaboration the control modes are: (a) position control mode, P; (b) high impedance control mode, HI; (c) medium impedance control mode, MI; (d) low impedance control mode, LI; and (e) force control mode, F. . . 62
3.6 Position control algorithm. The error of each joint (✓error) passes through
a position controller box, which is a proportional controller whose param-eters are individually selected for each joint of the exoskeleton. . . 62
3.7 Changes in reference trajectories (✓ref) for hip, knee and ankle
flexion-extension depending on di↵erent parameters as percentage of ROM ap-plied and gait speed. . . 64
3.8 Impedance control algorithm. Two loops compose the impedance algo-rithm, treating the error generated through two controllers: position con-troller box and torque concon-troller box. The parameters of each concon-troller are individually selected for each joint. . . 65
3.9 Di↵erent levels of impedance control strategy depending on the assis-tance provided: (a) high impedance, (b) medium impedance and (c) low impedance. Similar values of references (blue lines) and forces (green lines) cause diverse real trajectories (yellow lines) according to the type of impedance level. . . 66
3.10 Force control algorithm. The measured force for each joint of the ex-oskeleton is compared to a force to overcome selected by the clinician. The error is adjusted depending of movement (flexion or extension), and subsequently, it passes through a force controller box whose parameters are individual for each joint. . . 68
3.11 100 s capture data from a technical validation with a patient with CP (GMFCS level IV), using position control (P) on the knees and high impedance control (HI) on the hips. Blue lines represent the reference trajectories provided by the mathematical models implemented in CP-Walker; yellow lines are the real movements described by the user’s lower limbs; finally, green lines denote the measures of the strain gauges in case of impedance control.. . . 69
3.12 60 s capture data from a technical validation with a second patient with CP (GMFCS II), following medium impedance (MI) for all the joints of the exoskeleton. Blue lines represent the reference trajectories provided by the mathematical models implemented in CPWalker; yellow lines are the real movements described by the user’s lower limbs; finally, green lines denote the measures of the strain gauges in case of impedance control. Impedance mode for knee joints is only available during swing phase of gait. . . 70
3.13 Adaptive impedance controller of CPWalker. Brown square is the cal-culation block, where the user’s performance is analysed based on the achievement of % in Tevaluation. When new is determined, it needs to
be chosen from the five control modes of CPWalker (blue square). The control signal produced by the control mode is sent to CPWalker joint (green square) in order to produce the movement.. . . 73
3.14 Right hip interval of 70s selected from the user’s performance with CP-Walker using the multi-joint adaptive impedance controller. (a) represents the comparison between the percentage achieved by the user each 3 steps (pink line) respect to the desired challenge % (blue line). (b) shows the change of new (pink line) each 3 steps (blue line) depending on the
percentage in (a). (c) is the graph of the user’s performance: yellow line is the real motion and blue line is the set point. . . 76
3.15 IMUs based interface to give biofeedback of postural control in head and trunk. The graphics show IMUs data collected in real time for head and trunk in three planes (blue lines), and these were compared with hip ROM (red lines). The red squares represent postures out of the limit values (acoustic feedback playing). . . 79
3.16 Patient’s trunk kinematics during the pilot technical experiment. Normal trunk kinematics data is represented in grey. Pre-intervention data is represented through dotted lines. Post-intervention data is represented through continuous lines. Left side in red and Right side in green. . . 79
3.17 Schematic view of the methodology used for the CPWalker graphic interface. 80
3.18 Windows of the Clinical Application developed to control CPWalker plat-form. . . 82
3.19 Evolution of therapy parameters in P1. Blue line is the percentage of amplitude of the range of motion programmed in the robot. Yellow line corresponds to the percentage of the patient’s body weight that is sup-ported by the platform. These parameters were adjusted individually during the treatment in order to tailor the therapy to each patient. . . 85
3.20 Outcomes from kinematic analysis in patients P1, P2 and P3 without robotic aid. The graphics show the improvements for each patient de-pending on the focus of each therapy. Green lines are referred to right side and red lines to left side. Dashed lines correspond to 3D studies done before the robotic treatment and continuous lines to 3D studies done after five weeks of robot-based therapy.. . . 88
3.21 Overview of the performance-based adaptive controller adjusted for LOPES II gait trainer. User’s performance is evaluated based on the di↵erence between measured (✓) and reference (✓ref) joint angles for each subtask
j and in each leg separately, looking at some “key points” of the gait cycle (deviations at black dots in “Performance-based evaluation” box). The performances per subtask are compared to the challenge and toler-ance ( ± tol) after a specific number of steps (Tevaluation), and based on
this, a new level of assistance (klevel,j from 0% to 100%) is applied for
each subtask. Depending on the subtask of gait that is assisted, specific assistance profiles are applied by the robotic gait trainer (green lines in “Subtask-based profiles” box).. . . 90
3.22 E↵ects of various amounts of PBWS on mean joint angles for ten healthy users walking at 0.4m/s when no robotic assistance was provided. Black dots indicate key points for each subtask. . . 95
3.23 E↵ects of various amounts of PBWS on right step length for ten healthy participants when no robotic assistance was provided. . . 95
3.24 Gait performances determined with (1) in ten healthy users for diverse subtasks of walking in two situations: i) when no robotic assistance is applied (unfilled blue boxes), and ii) when the performance-based con-troller applied robotic assistance (filled blue boxed). The applied robotic assistance is represented in % (red boxes). Within each subtask, various amounts of gait speed and PBWS were evaluated. . . 98
4.1 Overview of the training protocol and main gait functions that need to be covered. . . 103
4.2 Robot-based training program overview. First phase: sessions S1 to S8 for strength exercises where motor control was primary trained. Second phase: sessions S9 to S16 for power training where the assistance was progressively decreased with the patient’s progression. The improvements were assessed at three stages of analysis: before treatment begins, between both phases and at the end of the program (grey ellipses in the figure).. . 107
4.3 First phase: strength training progression values along first 8 sessions of the robot-based therapy. Trajectory tracking motion was imposed by the robot. Blue line represents the movement amplitude (%ROM), yellow line gives the changes of %PBWS and the green line is referred to gait velocity percentage for each session. . . 108
4.4 Second phase: power training progression values along sessions 9 to 16 of the robot-based therapy. Six di↵erent levels of assistance were selected on the exoskeleton (combining hips and knees). Blue line represents the movement amplitude (%ROM), yellow line gives the changes of %PBWS and the green line is referred to gait velocity percentage for each session. . 109
4.5 Representation of several patients working with CPWalker in di↵erent session performance: (a) Patient in session 1 of first phase (with 100% of PBWS) receiving motion feedback from a screen located in front of her; (b) Patient in session 1 of first phase (with 100% of PBWS) wearing a mask on his eyes in order to enhance the motion feeling; and (c) Patient during over-ground walking performing one of the session of the study. . . 109
4.6 Levels of assistance (L1 to L6) depending on the patient (P4 to P7) and the AAN session (S9 to S16). The patients could jump to the next level if they achieved at least the 85% of the pattern desired for each session. The level for P7 in S11 is not represented because P7 lost this session. . . 116
4.7 (a) Results of GMFM-88 (D and E dimensions), (b) SCALE, (c) 6 mwt, and (d) 10 mwt in pre, middle and post analysis for all the patients (P4 to P7). The SCALE was measured bilaterally (left and right). The 10 mwt was performed in two situations: comfortable speed (Comf) and maximum speed (Max). . . 117
4.8 Comparison between middle and post analysis related to the PCI, calcu-lated as a parameter to express the energy cost expended by the patients in the walking distance during the 6 mwt. . . 117
4.9 Maximum strength measures recorded for all the patients in pre (the light-pink line), middle (the dark-light-pink line) and post analysis (the purple line). Both legs were evaluated, right (R) and left (L). . . 118
4.10 (a) GPS and (b) GDI for pre, middle and post kinematic analyses of pa-tients P4 to P7. The results represent means± standard error bilaterally (left in red bars and right in green bars). Normality in GPS considers val-ues lower than 7 points (doted-black line in (a)), and normality in GDI comprehends values higher than 100 points (doted-black line in (b)). . . . 119
4.11 ROM performance of some steps walking with CPWalker in two situa-tions: (a) Session 3 for patient 4 (first phase of the training with tra-jectory tracking) and (b) Session 16 for patient 4 (second phase of the training through AAN strategies with level 5 of assistance (LI at hips and MI at knees)). . . 121
5.1 Recommended use (training coverage) of CPWalker and other RAGT as a function of FAC. . . 127
1.1 Types of movement disorders in CP according to Surveillance of Cerebral Palsy in Europe (SCPE) . . . 8
1.2 Overview of devices for CP focused on upper limbs . . . 18
1.3 The most relevant robotic platforms for lower limbs in CP . . . 23
1.4 Main characteristics and shortcomings in current robotic devices for gait rehabilitation of children with CP. The gait exercises can be implemented through over-ground walking (OW), treadmill training (TT) or foot plates (FP), depending on the device . . . 24
2.1 Descriptive parameters of the sample for interview . . . 30
2.2 Estimated power for human flexion-extension movements during normal walking . . . 34
2.3 Main aspects and principal advantages of current robotic devices for gait rehabilitation in CP . . . 34
2.4 Prioritized DOFs in CPWalker platform. The type of actuation might be: powered (P), free (F), or constrained (C) . . . 37
3.1 Data for all the joints during the period of 70 s selected from the exercise with the healthy user. G0 to G6 are the groups of 3 steps implemented during this period. The table gives the progression of new depending on
the % achievedin the last group of steps. Bold values represent % achieved
> % , and (*) means % achieved > 100% because the user’s
flexion-extension set was bigger than that given by the set point. . . 76
3.2 Description of the patients recruited for a preliminary clinical training with CPWalker robotic platform . . . 84
3.3 Selected parameters according to the patients’ capabilities . . . 86
3.4 Comparison between Pre and Post studies: spatial-temporal parameters and kinematics related to the selected improvements for each patient (cor-respondence with Figure 3.20). (⇤) corresponds to trunk rotation assess-ment and (⇤⇤) to hip flexion-extension . . . 87
3.5 Supported movements and gains for diverse subtasks of gait to calculate performances using Equation 3.15. Assistance profiles (green lines) ap-plied for each subtask are shown with respect to the joint angle for hip or knee (blue lines). . . 91
3.6 Overview of trials to test the e↵ects of walking speed and PBWS on the behaviour of the adaptive controller in LOPES II. . . 93
3.7 p-values for the 2-way repeated measures ANOVA for each subtask of gait. (*) indicates significant di↵erences with p < .05 and (**) significant di↵erences with p < .001. . . 96
4.1 Goal settings of the ICF-CY and the robot-based solutions adopted with CPWalker platform . . . 105
4.2 National Strength and Conditioning Association (NSCA) youth training guidelines . . . 106
4.3 Levels of assistance in first and second training phases: Position (P); High Impedance (HI); Medium Impedance (MI); Low Impedance (LI). The assistance on knee joint always went behind the assistance on hip, due to the knee movement during gait is performed following inertial forces, assigning to the hip movement higher importance. A higher level is implemented if the session performance (real motion versus desired pattern) is bigger than 85% . . . 110
4.4 Evaluation metrics and moment of application . . . 112
4.4 Continuation of Table 4.4 . . . 113
4.4 Continuation of Table 4.4 . . . 114
4.5 Patients’ description. Two females (F) and two males (M) with spastic diplegia were selected. No medication 3-months prior the study was taken by the patients. The type of walking support without the aid of the robot is indicated for a distance of 50m and 500m: crutches-CT, wheelchair-WC, posterior walker-PW and cane. . . 115
4.6 Spatial-temporal parameters, GPS and GDI values for pre, middle and post analyses in all the patients. Results were calculated taking an average of 40 steps . . . 120
AAN Assist-As-Needed AFO Ankle Foot Orthoses BCI Brain-Computer Interface BMI Brain-Machine Interface CAN Controller Area Network CNS Central Nervous System CP Cerebral Palsy
CSIC Spanish National Research Council CSTs Corticospinal Tracts
CT Crutches
DOFs Degrees of Freedom EEG Electroencephalography EMG Electromyography
F Force control mode
FAC Functional Ambulation Category FES Functional Electrical Stimulation FMS Functional Mobility Scale
FO Foot Orthoses
FSR Force-Sensing Resistor GGI Gillette Gait Index
GMFCS Gross Motor Function Classification System GMFM Gross Motor Function Measure
gNEC Neural and Cognitive Engineering group HI High Impedance control mode
HKAFO Hip Knee Ankle Foot Orthoses HNJ Ni˜no Jes´us Hospital
HSP Hereditary Spastic Paraparesis IBV Biomechanical Institute of Valencia
ICF-CY International Classification of Functioning,
Disability and Health framework, Children and Youth version xxxi
IMUs Inertial Measurement Units KAFO Knee Ankle Foot Orthoses LI Low Impedance control mode LRF Laser Range Finder
MA Melbourne Assessment
MACS Manual Ability Classification System MAS Modified Ashworth Scale
MHRI Multimodal Human-Robot Interface MI Medium Impedance control mode
NINDS National Institute of Neurological Disorders and Stroke NSCA National Strength and Conditioning Association
P Position control mode
PBWS Partial Body Weight Support PCI Physiological Cost Index
PEDI Pediatric Evaluation of Disability Inventory PNS Peripheral Nervous System
PW Posterior Walker
PWM Periventricular White Matter
QUEST Quality of Upper Extremity Skills Test RAGT Robotic-Assisted Gait Training
RIC Rehabilitation Institute of Chicago ROM Range Of Motion
SCALE Selective Control Assessment of the Lower Extremity SCI Spinal Cord Injury
SCPE Surveillance of Cerebral Palsy in Europe SEMLS Single Event Multilevel Surgery
TRL Technology Readiness Level UT University of Twente VR Virtual Reality
WC Wheelchair
F Measured force
Ferror Error force Fref Reference force Gj Subtask-specific gain j Specific subtask of walking k Sti↵ness of robotic assistance P erf Performance
RG Rotation matrix capture at the time of calibration RS Rotation matrix captured in each instant
Tevaluation Evaluation time of performance
tol Tolerance
↵ Euler angle in frontal plane Euler angle in sagittal plane Euler angle in transversal plane
✓ Measured angle
✓error Error angle ✓ref Reference angle
def ault Default control mode new New control mode
Organization of Work
All of us were born with limitations, which we are continuously overcoming by the acquisition of capabilities during childhood, adolescence and adulthood. The faculty to obtain these capabilities depends on each person, being very often related to the person’s attitude towards challenges of life. People with disabilities have major challenges to face during their development, however, the term “disability” is referred to the difficulty to carry out particular or specific activities, but it never means a total incapacity. People with disabilities are also full of skills and possibilities for the future, which in most of the cases will get better with e↵ort.
Cerebral Palsy (CP) is the most frequent disability in childhood [1, 2]. It is caused by abnormal development or damage to parts of the brain, which very often are responsible of control movement, balance or posture, and to a lesser grade, they a↵ect sensory or cognitive mechanisms. CP in childhood is associated with heavy demands on health, educational and social services, as well as on families and children themselves.
Early and ongoing rehabilitation treatments look for the improvement of capabilities of people with CP. The main therapies are [3]: i) physical and occupational therapy, which is focused on walking, standing, stretching exercises, and flexibility; ii) oral medication, which is generalized to spasticity treatment; iii) orthoses, which are normally used in chil-dren with CP to try to prevent deformities, contractures, and pain; iv) botulinum toxin to treat localized spasticity; v) ferule and plaster to avoid moderate contractures; vi) multilevel orthopedic surgery, which consists in two or more soft-tissue or bony surgical procedures, at two or more anatomical levels during one unique operative procedure [4]; vii) partial body weight-supported treadmill training and constraint-induced movement therapy, which are based on motor learning theories and promote the standardization of gait pattern by involving sensory information and reflection components of gait; and viii) Robot-Assisted Gait Training (RAGT), which may be an e↵ective tool to compensate or rehabilitate the functional skills of people with CP [5].
In particular, rehabilitation robotics has been an emerging research field in the last years [6]. RAGT shows some promising advantages compared to conventional therapy [7], however, it should be further improved to increase its e↵ectiveness, enhance motor learning and enrich recovery [7,8]. The improvements of RAGT begin with the integra-tion not only of Peripheral Nervous System (PNS) but also of Central Nervous System (CNS) into the human-robot loop. The parallel integration of both systems maximizes the therapeutic e↵ects arising from the brain plasticity, which may be understood as the ability of the brain to change and thereby adapt the nervous system to physiologic changes and experiences [9]. Although this approach has been previously studied in other populations (e.g. Spinal Cord Injury (SCI) [10]), nowadays there is a lack of stud-ies in CP [6]. On the other hand, recent studies suggest that RAGT should also include user’s motivation and cognitive aspects as the attention as essential points to achieve a higher impact in physical abilities. In that sense, techniques that involve cooperative tasks (virtual reality (VR), training in real-life scenario or exercises with challenges for the patients) are being used, but still under development [7].
The main purpose of this work is to design, develop and evaluate a new robotic platform to improve the gait function of children with CP. Moreover, the author defines di↵erent strategies to implement into the robotic platform to be part of rehabilitation clinical protocols with children with CP. It is important to highlight that the target patients of this thesis (young children) have greater brain plasticity than adults [11], and are more likely to have a change in motor patterns following an intervention. According to this fact, it is essential to propose them physical exercises that increase their attention and motivation, delivering direct and causal feedback throughout the therapy. In order to fulfil the previous requirements and to provide a better solution for children with CP, various objectives are given below, which pursue two main goals: first, to design a new robotic platform that manages to improve the traditional gait rehabilitation; and second, to introduce new concepts and guidelines to allow novel therapies into the rehabilitation field. In a nutshell, the proposed objectives are:
• To develop a new robotic platform to support new therapies for gait rehabilitation of children with CP.
• To elaborate novel rehabilitation therapies based on the robotic platform in order to improve the traditional rehabilitation, tailoring the therapy to the patient’s needs.
• To provide means for an objective evaluation of the robot-based rehabilitation therapies, based on the evaluation of the gait kinematic patterns, functional as-sessment and synergies generated.
• To validate the functional and usability benefits of the proposed robotic concept with final users (clinicians and patients).
• To evaluate the practical feasibility of the new system in clinical practice.
• To compare patients treated with traditional therapies with the ones treated with the therapies developed with this novel device.
Four hypotheses support these previous objectives:
• The rehabilitation with the proposed device will engage the users throughout ther-apy sessions. Patients will enhance their interest and motivation if the exercises are challenging, and thereby, the treatment outcomes will become better. With this goal, the device will use di↵erent technologies through which the CNS and PNS will be introduced in the rehabilitation.
• The ambulation treatment in real rehabilitation environments is a more challeng-ing exercise than the rehabilitation on treadmill. If the patient’s motivation is higher, the intensity and frequency of the therapy will increase. Moreover, chil-dren might create new brain connections and develop cognitive skills by exploring the world around them. This means that spatial cognition, problem solving and depth perception will be upgraded, which implies improvements in the outcomes of the treatment.
• The inclusion of novel algorithms to correct the child’s posture and to enable the definition of tailored therapies for each patient will promote user’s participation and may impact on brain reorganization.
• The early use of assistive technology in children with CP is considered a parameter of paramount importance to the results of the therapy. It is during these ages when brain plasticity is at its highest level, leading to the maximum capability for physical and cognitive rehabilitation.
Organization of work
The proposed methodology to achieve the objectives described in the previous section is based on an in-depth bibliographical study related to di↵erent fields of CP, in particular, technology used for gait rehabilitation. The work is divided into five chapters that partially overlap with the principal publications derived from the thesis [3,12–14]. The chapters are organized as follow:
First chapter presents a general review of the state-of-the-art of CP rehabilitation. It starts describing the CP term and analysing the possible classification groups depending on di↵erent approaches. Subsequently, the chapter exposes an extensive review of the current treatments for patients with CP, with special emphasis on robotic rehabilitation [3]. The state-of-the-art of robotic devices for rehabilitation in CP is presented at the end of chapter1. The rest of the dissertation is based on this preliminary research. Although several existing robotic devices attempt to improve the gait training of chil-dren with CP and similar neurological and motor disorders, new challenges in robotic rehabilitation are needed in order to ratify its e↵ectiveness and enrich current training protocols [7,8,15]. In this regard, chapter2 establishes the main requirements for the development of a novel robotic platform for gait rehabilitation in CP. Both the me-chanical design and control architecture of the platform are described in this chapter, going into detail about the di↵erent incorporated systems and their interaction [12]. The conclusions of chapter 2 will serve as the base to develop new algorithms and control strategies to implement innovative robot-based therapies.
The third chapter is focused on the definition and technical evaluation of elemental control strategies for robotic gait training in pediatric population. These strategies are based on a Multimodal Human-Robot Interface (MHRI) that makes the interaction between the patient and the robotic device. The control strategies are defined and evaluated using the gait trainer of this thesis, but they could also be applied to other rehabilitation platforms. Indeed, at the end of chapter 3, the author exposes how a controller developed within the framework of this dissertation, has been transferred to other domains. A preliminary validation of the control strategies on real patients provided important outcomes to define a robot-based gait training proposal [13]. Chapter 4 covers the goal settings and detailed guidelines of an accurate robot-based program for gait rehabilitation of pediatric population with CP [14]. This rehabilitation program tries to improve patients’ capabilities related to diverse functional domains of the International Classification of Functioning, Disability and Health framework, Chil-dren and Youth version (ICF-CY) [16]. Two gait training phases (strength phase and power phase) are considered, which are validated in four children with CP as prelimi-nary support for future clinical implementations. At the end of the chapter, the author presents a discussion of the obtained results.
Chapter 5 summarizes the main conclusions and identifies major contributions of this work. Furthermore, it presents the future work derived from the outcomes of this dis-sertation.
Introduction to Cerebral Palsy
and Gait Rehabilitation
In the last decades, studies about rehabilitation in Cerebral Palsy have increased, plac-ing emphasis on promotplac-ing active therapies with high intensity and repetitive and task-specific training in order to enhance neuroplasticity. Robot-based treatment for gait re-habilitation is a novel approach, currently under development, which drives the patient’s gait in special conditions enhancing the progress of the therapy.
This chapter presents an overview of the Cerebral Palsy pathology, its main risk factors and classification scales. The chapter highlights the principal therapies carried out in re-habilitation of Cerebral Palsy, and focuses on emerged robotic technologies reviewing the current devices used with this aim. Finally, the chapter also identifies the main short-comings on current robotic trainers in order to define a new device for gait rehabilitation in Cerebral Palsy and related disorders.
1.1
Cerebral Palsy
CP term could be defined, according to the National Institute of Neurological Disorders and Stroke (NINDS), as “any one of a number of neurological disorders that appear in infancy or early childhood and permanently a↵ect body movement and muscle coordi-nation but do not worsen over time”. These disorders can disturb other higher functions and infer in the CNS. Nevertheless, the definition of CP remains a controversial issue at the present time. The universal acceptance of one definition of CP does not exist, but it is often associated with sensory deficits, cognition impairments, communication and mo-tor disabilities, behaviour issues, seizure disorder, pain, and secondary musculoskeletal
problems [17]. Movement and posture disorders derived from CP are generally charac-terized by loss of muscle strength, improper muscle activation and loss of coordination [18].
This disease is more common in males, and the main causes and risk factors are: multiple birth, extreme prematurity, birth asphyxia, feeding issues, prolonged hospitalization, or postnatal infection [19]. So far, CP has been diagnosed between 12 and 24 months of age, but nowadays, it is possible an early diagnosis at 12 weeks of age for roughly half the a↵ected population, via the evaluation of risk factors previously given [19].
The overall rate of CP for the period of 1980 to 1990 was 2.08/1000 live births (95% CI 2.02 to 2.14) [20,21]. One in five children with CP (20.2%) had a severe intellectual deficit and was unable to walk. Among babies that weighed less than 1500 g at birth, the rate of CP was more than 70 times higher than those weighing 2500 g or more at birth. The rate of CP rose during the 1970s but remained constant during the late 1980s [21]. It was also maintained about constant from 1980s to through 2002, rather than increasing as might be expected [2]. The rate of multiple births in the population increased from 1.9% in 1980 to 2.4% in 1990, and the proportion of multiples among infants with CP increased from 4.6% in 1976 to 10% in 1990. Multiples have a four-fold higher rate of CP than singletons overall [20,22]. Recent studies affirm that the current prevalence of CP is 2.11/1000 births (95% CI 1.98-2,25) [1,2].
In the last years, the improvements in care during pregnancy and after birth have pre-vented cases of CP with severe intellectual disability (prevalence for these cases decreased about 2.6% each year from 1985 to 2002, [2]).
1.2
Classification of Cerebral Palsy
The CP term covers a quite heterogeneous groups of disorders, and therefore, it is difficult to classify the type of CP su↵ered by a patient. In accordance with the Spanish confederation for the care of people with CP [23], individuals with CP are normally categorized into classes or groups, though most people with CP have a combination or two or more types. From a topographic point of view, depending on how many structures are involved (see Figure 1.1), people with CP could be classified as having Hemiplegia, Paraplegia, Tetraplegia, Diplegia, or Monoplegia [23]:
• Hemiplegia: Only one side of the body a↵ected, including arm, leg and trunk. • Paraplegia: Lower limbs a↵ected.
• Diplegia: The most a↵ected limbs are the lower limbs. • Monoplegia: Only one limb is a↵ected, usually an arm.
This classification, used in combination with the type of movement disorder (Spastic-ity, Dyskinesia/Athetoid, Ataxia, or Mixed), o↵ers an interesting approach for clinical practice. Table1.1shows the description of each movement disorder in CP according to “Surveillance of Cerebral Palsy in Europe” (SCPE) [24].
On the other hand, functional classification procedures are recommended when a clinical decision is required. In order to categorize the degree of involvement, the most used scale is the “Gross Motor Function Classification System” (GMFCS) from Palisano et al. in 1997 [25], which was revised in 2007. It defines five levels of CP depending on functional limitations (Figure 1.2), the need for hand-held mobility devices (such as walkers, crutches or canes) or wheeled mobility, and to a much lesser extent, quality of movement. This bibliography also recognizes that the levels of GMFCS are based on age (groups under two years old, between two and four years old, between four and six years old, between six and 12 years old and between 12 and 18 years old):
• Level I: Walks without limitations.
• Level II: Walks with limitations in long distances and balancing. They may need a hand-held mobility device to learn to walk for the first time. They require some support to walk up and down stairs.
• Level III: Walks using a hand-held mobility device.
• Level IV: Self-mobility with limitations. They may use powered mobility. • Level V: Has severe limitations in head and trunk control. They are transported
in a manual wheelchair, and self-mobility is only achieved if the child is able to learn how to operate a powered wheelchair.
Table 1.1: Types of movement disorders in CP according to Surveillance of Cerebral Palsy in Europe (SCPE)
Spastic CP
- Abnormal pattern of posture and/or movement. - Increased tone.
- Pathological reflexes.
- Spastic CP may be either bilateral or unilateral:
· It is bilateral if limbs on both sides of the body are involved. · It is unilateral if limbs on one side of the body are involved.
Dyskinetic or Athetoid
CP
- Involuntary, uncontrolled, recurring, occasionally stereotyped movements.
- Abnormal pattern of posture and/or movement. - Spastic CP may be either dystonic or choreo-athetotic:
· Dystonic CP is dominated by both hypokinesia and hypertonia. · Choreo-athetotic CP is dominated by both hyperkinesia and
hypotonia.
Ataxic CP
- Abnormal pattern of posture and/or movement.
- Loss of orderly muscular coordination used to perform movements with abnormal force, rhythm and accuracy.
Mixed CP - Combined several types of CP.
Another evaluative method is the “Functional Mobility Scale” (FMS) [26], which is uti-lized to measure functional mobility over three distinct distances (5 m, 50 m and 500 m), specifying the assistive device that the child needs to use. In line with the GMFCS and the FMS, severity is also used for classification purposes (Moderate, Moderately severe, or Severe CP).
Finally, taking into account the measure on fine motor function, the “Manual Ability Classification System” (MACS) [27] classifies the use of hands in users with CP to perform activities of daily life. Other scales as “Modified Ashworth Scale” (MAS) or “Tardieu Scale” have the purpose of measuring spasticity in patients with CP. They are a quick and easy form that can assist a clinician’s assessment of spasticity during passive soft-tissue stretching.
However, in spite of all these metrics, in most cases it is difficult to classify a patient due to the wide variety of alterations and levels of severity.
Figure 1.2: Levels of Gross Motor Function Classification System (GMFCS).
1.3
Current therapies for patients with CP
A complete cure for CP is not currently available, because this means repair of the underlying brain damage. Therefore, rehabilitation is commonly used with the princi-pal aim of improving patient’s independence in daily life [6] and preventing secondary complications. If secondary musculoskeletal disorders appear and they are persistent, some factors emerge such as gait impairments, abnormal muscle tone, fatigue, weakness, communication impairments and loss of function.
Therapies for CP and their mode of application depend on the specific patient’s disorders and severity, and they range from physical therapy to medication and surgery. However, under all conditions, rehabilitation needs to be implemented during the early stages of child’s development, because it is at this phase when fundamental abilities and skills are developed [28]. These abilities include activities of daily living as playing, self-care activities and fine motor tasks (writing, reading or drawing). The success rate of rehabilitation also increases in accordance with the intensity of therapy, repetition, and patient’s motivation, the latest specially in children [6]. As a result, it is essential to give children with CP the opportunity to interact with the environment looking for an integral development (physical and cognitive).
The estimated cost to care for an individual with CP is a real problem for families and caregivers, and it is around $1 million. The combined estimated lifetime costs for all people with CP who were born in 2000 will total $11.5 billion in direct and indirect costs [22].
Next subsections summarize the main therapies carried out so far for rehabilitation of people with CP [3].
1.3.1 Physical and occupational therapy
Physical therapy is a part of rehabilitation that tries to restore, maintain and promote patient’s optimal movement and physical function. The main goal of the physical therapy is to maximize functional control of the body, or increase gross motor function. There are a wide variety of exercises that are carried out in physical therapy for CP [29], but in general, they are focused on walking, standing, stretching exercises, and flexibility. Physical therapy should be always guided by a physiotherapist, who can benefit from di↵erent instruments as bars, treadmill and other adaptive equipment designed to achieve mobility, but also could involve robotic devices to implement the exercises. In the last case, it is called “robotic physical therapy”.
1.3.2 Oral medication and botulinum toxin
Some drugs could be indicated in CP cases in which the distribution of muscle overactiv-ity is di↵use. In particular, the main current approved agents to treat spasticoveractiv-ity in CP are baclofen and diazepam. From the end of 20th century, botulinum toxin type-A has been used to complement the existing oral medication for treating spasticity, mainly fo-cused on motor problems of children with CP [30]. The principal di↵erence between both oral medication and botulinum toxin is that the e↵ects of the latest could be localized for a specific region of the body.
1.3.3 Orthoses and technical supports
Technical support is defined as any product developed with the aim of preventing, com-pensating or neutralizing activities limitations or restrictions in the participation. De-vices for gait technical support in CP are primarily designed to allow autonomous dis-placement to the patient, improving functional independence and social integration. In a second way, they try to prevent deformities, contractures, and pain. As a consequence, user’s quality of life is changed for the better.
The whole of technical aids in children with CP is extremely diverse, and it may range from orthoses (Figure 1.3) to canes, crutches and walkers (Figure 1.4):
• Orthoses: They are external supports that can be adapted individually for each patient. Their aim is to modify the structural or functional conditions of the neu-romusculoskeletal human system. In CP, orthoses are normally used to reinforce and protect a surgical procedure during a rehabilitation period. With them, the
Figure 1.3: Types of orthoses for children with movement disorders. (a) Foot orthoses (FO); (b) Ankle Foot orthoses (AFO); (c) Knee Ankle Foot orthoses (KAFO); (d) Hip
Knee Ankle Foot orthoses (HKAFO).
development of growth abnormalities are limited and the gait is improved [31]. There are some types of orthoses depending on the body segment that is utilised:
– Foot orthoses (FO): Normally used as insoles, Figure 1.3(a).
– Ankle Foot orthoses (AFO): The most applied in CP to prevent equinus foot, Figure 1.3(b).
– Knee Ankle Foot orthoses (KAFO): They are not very common in CP treat-ments, Figure1.3(c).
– Hip Knee Ankle Foot orthoses (HKAFO): They are rarely used today in chil-dren with CP. They control lateral movements and spasticity, Figure1.3(d). • Walkers: They are useful devices to assist people in walking actions. For its use, it is necessary the presence of motor control as the patient’s capacity of head control and weight discharge in lower limbs [32]. There are some types of walkers, but the most used are anterior walkers (positioned in front and moved forward by the user, Figure 1.4(a)) and posterior walkers (the person pulls from behind, Figure 1.4 (b)). Some studies in the bibliography affirm that posterior walkers have more advantages in terms of upright positioning and energy conservation than anterior walkers [33]. Moreover, posterior walkers could be more favourables since the person’s center of mass is within the base of support of the walker.
1.3.4 Orthopaedic surgery
Most of current basic treatments applied with the aim of improving the mobility in patients with CP, are not e↵ective at some specific age (observe Figure1.5) [34]. With the child’s growth, deformities in bones increase, and muscles on hip, knee and ankle work in a worse way contributing to the development of crouch gait (Figure 1.6). The progress
Figure 1.4: Types of walkers for children with movement disorders. (a) Anterior walker; (b) Posterior walker.
of crouch gait linked to a pubertal growth spurt, generates knee pain, a decrement of endurance, and the necessity of using gait assistive devices [4].
To address the limitation of progressive musculoskeletal disorders, orthopaedic proce-dures have been designed. One of the most important concepts in this field is the “Single Event Multilevel Surgery” (SEMLS), adopted by Nene et al. in 1993 [35]. It may be understood as a type of surgery in which multiple levels of musculoskeletal pathology in both lower limbs are addressed by two surgical teams during only one operative proce-dure. It requires only one hospitalization and one rehabilitation period [4,34,36]. The
Figure 1.5: Treatment applied during the growth of children with CP. Frequency peak for SEMLS is achieved in puberty stage.
Figure 1.6: Sti↵ knee flexo in a patient with CP.
most common gait pattern treated with SEMLS corresponds with crouch gait combined with knee flexion, hip flexion and ankle dorsi-flexion [32].
SEMLS technique has demonstrated important benefits in musculoskeletal problems of children with CP, reducing walking e↵ort [35], improving the “Gross Motor Function Measure” (GMFM) [37, 38] and kinematic parameters [39], gait speed [40] and the Gillette Gait Index (GGI) [41]. However, it should be only applied if conservative treatments were not enough to stop the progressive deterioration of patient’s ambulation. Current conventional rehabilitation techniques after a surgical procedure in CP are mainly carried out in four stages, which following chronological order in rehabilitation period, they are: i) in first phases after surgical process we found early mobilization, cryotherapy, active and resisted kinesiotherapy of non-operated limb and isometric con-traction of operated limb; ii) analytical and resisted kinesiotherapy of operated limb, stretching exercises and trunk and postural control exercises; iii) in more advanced re-habilitation stages we found dissociation of limbs, weight transfer exercises and changing between sitting and standing position; and iv) muscle strengthening machine, balance exercises, squats, stairs and parallel bars.
1.3.5 Robotic physical therapy
Recently, several technological advancements have been introduced into the field of re-habilitation to complement conventional therapeutic interventions. In the light of this, robot-assisted therapy appears as an alternative and complementary treatment [6]. It could be defined as a form of physical therapy that uses a non-invasive robotic device to help a person with an impaired functional ability to recover their function [42]. Robot-assisted training increases the therapy compliance by proposing goal-directed tasks that
encourage the patients. This approach has interesting advantages compared to tradi-tional therapy, because it suggests functradi-tional exercises with accurate and assembled movements, instead of repetitive movements without goals. Moreover, robotic trainers reduce the physical load and cost of conventional therapies, integrating at the same time novel systems to objectively measure the progression of the exercise. As a result, the number of sessions, frequency, intensity, and finally the positive impact of the treatment are typically increased.
Robotic devices may sometimes be combined with new and advanced methods of feed-back, as the application of virtual scenarios, where the users can interact with a virtual object in real-time and feel that they are part of a virtual environment during the ther-apy [6,43]. In that sense, there is widespread interest in using VR in the rehabilitation of children with CP to address upper [44,45] and lower extremity motor functions [46,47]. On the other hand, robot-assisted gait therapy is also often combined with partial body weight support (PBWS) [48–50], providing beneficial results specially in patients with low ambulatory status. This feature allows repetitive execution of gait movements in a controlled and safe way, with an adjustable support of body weight, which is sometimes in high demand by the therapists. Generally, training protocols include a gradual increase of difficulty level by decreasing the amount of PBWS provided during walking.
Nevertheless, although some features of using robot-based therapies have demonstrated positive results compared to traditional training in di↵erent pathologies, there is a weak evidence regarding the use of RAGT in case of children with gait disorders [8, 51]. With the main aim of addressing this fact, this thesis proposes a novel solution based on robotic rehabilitation as part of the gait training for patients with CP. In order to better understand the robotic field, and to know the existing alternatives, next section gives an (incomplete) overview of robotic devices that are currently used for rehabilitation of children with CP, both upper and lower limbs. This will serve to discuss the challenges that are needed to fulfil, and it will provide the background for a new proposal of robotic gait trainer.
1.4
State-of-the-art of robotic devices for rehabilitation in
CP
Robotic rehabilitation has been a growing research field in the last years. Most of the robotic devices were initially designed for spinal cord injury or stroke patients, and they are being recently adapted for people with CP. Within CP, pediatric population with CP is one of the last groups in which these technologies are being applied. In this case, there
is still no standardization about clinical conditions, time or outcome measures used. For this reason, it is difficult to describe and precisely quantify the benefits of robot-based therapy in children su↵ering of CP. Additionally, a more detailed description of user’s profile is required, specially in case of users with CP, whose motor particularities are very heterogeneous.
This section gives a general overview of the current robotic devices to implement reha-bilitation in CP. According to that, both cases upper and lower limbs are necessary to be reviewed to understand the last advances in robot-assisted rehabilitation for CP. The review provides a framework to finally identify the lacks in devices for lower limbs in order to look for a better robotic solution for gait rehabilitation of children with CP.
1.4.1 Robot-assisted rehabilitation for upper limbs
There are currently a limited number of robotic systems targeting the upper extremity that have been applied to children with CP [52]. These devices work via goal-directed tasks and reaching movements to rehabilitate hand and arm function.
The InMotion2 (Figure1.7(a)), also called the shoulder-elbow robot, is an end-e↵ector robot, a commercial version of MIT-MANUS (Interactive Motion Technologies, United States) [53], which is capable of continuously adapting to and challenging each pa-tient’s ability. This device aims to improve the papa-tient’s range of motion, coordination, strength, movement speed, and smoothness. 117 subjects that had previous strokes were trained with InMotion2, and during the training patients were able to execute shoulder and elbow joint movements with significantly greater independence. At the end of the experiment, the subjects were better able to draw circles [54]. In most cases, studies conducted with stroke patients have encouraged new experiments with people with CP, as in another experiment where 12 children aged 5-12 years with CP and upper-limb hemiplegia received robotic therapy twice a week for 8 weeks. The children showed sig-nificant improvement in their total Quality of Upper Extremity Skills Test (QUEST) and Fugl-Meyer Assessment scores [53]. Following the distal approach, Interactive Motion Technologies developed the MIT-Manus InMotion3, which works with flexion, exten-sion, pronation, and supination of the a↵ected wrist. The results are similar to those of InMotion2, but in this case, InMotion3 can operate both as a standalone device and as an InMotion2 module; InMotion3 has not yet been used in studies that include children with CP.
Another robotic system for the upper limbs is the New Jersey Institute of Technology’s Robot-Assisted Virtual Rehabilitation System. It is comprised of a HapicMaster and a custom-made ring gimbal (represented in Figure 1.7 (b)). This system has 6 Degrees
